Wisdom of crowds and commodity pricing
从推特数据提取大宗商品层面的情绪指标，发现基于情绪变化的交易策略能显著提升夏普比率，情绪溢价在宏观收缩和流动性恶化时更明显，且3年后完全反转。
Abstract We extract commodity‐level sentiment from the Twittersphere in 2009–2020. A long–short strategy based on sentiment shifts more than doubles the Sharpe ratio of extant commodity factors. Commodities with lower (higher) sentiment shifts tend to be overvalued (undervalued) when the aggregate market is in backwardation (contango). The sentiment premium is more pronounced during periods of macro contraction and deteriorating funding liquidity. While the premium concentrates in commodities with higher tweet intensity, sentiment extracted from influential tweets (i.e., high number of retweets/likes) does not exhibit stronger predictive ability than low‐attention tweets. Consistent with the overreaction hypothesis, the sentiment premium fully reverses 3 years postformation.